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combinatorial optimisation: Research in randomised optimisation algorithms, including evolutionary algorithms, tabu search, and many other approaches also collectively known as meta-heuristics, has long favoured
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neighbourhood exploration in combinatorial optimisation: Research in randomised optimisation algorithms, including evolutionary algorithms, tabu search, and many other approaches also collectively known as meta
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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Develop decision-support models for planning, scheduling, and supply chain management using advanced Operations Research, optimization
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INESC COIMBRA - INSTITUTO DE ENGENHARIA DE SISTEMAS E COMPUTADORES DE COIMBRA | Portugal | 3 months ago
algorithms, population-based methods, hybrid strategies, and decomposition approaches. The integration of machine learning and surrogate modeling techniques will also be explored to accelerate the optimization
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configurations and DNSSEC security validations. Implement the Kea DHCP service (or an equivalent solution) with a database backend. Develop APIs for migrating static data and test HA and failover algorithms
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; develop and validate an astrodynamics-based orbit determination algorithm using TFC, including hybrid solutions with stochastic filters (eg, EKF or UKF); integrate and calibrate optical sensors and develop
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 3 months ago
experience in Computational Bioimaging Methods based on image-processing algorithms for the automated integration of cellular phenotypic and molecular characteristics. Previous involvement in Research Projects
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layers and data processing ; 2) Development of machine learning algorithms for traffic characterization and damage detection; 3) Development of a toolbox for the automatic data acquisition and
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to create accurate cell charging and discharging models. 3. Development of Estimation Algorithms: Create algorithms to accurately estimate the state of charge (SOC) and state of health (SOH) of batteries. 4
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from users and participating academies. They will be responsible for evaluating the performance of personalized training plan recommendation algorithms, predictive models of user evolution, and class